Generative artificial intelligence in FinTech: Applications, environmental, social, and governance considerations, and organizational performance: The moderating role of ethical dilemmas

Authors

DOI:

https://doi.org/10.24136/oc.3323

Keywords:

FinTech sector, generative AI, TOE framework, ESG, China

Abstract

Research background: Generative Artificial Intelligence (GenAI) is a disruptive technology with great promise for the FinTech industry. The current study focuses on the drivers of GenAI adoption and its consequences for both exploratory and exploitative innovation in FinTech companies.

Purpose of the article: Based on a conceptual model that extends the Technology-Organization-Environment (TOE) framework, this study also explores the moderating effect of ethical dilemmas in the relationship between GenAI adoption and innovation, as well as the role of Environmental, Social, and Governance (ESG) factors in shaping the broader impact of GenAI on organizational practices.

Methods: Data were collected and analyzed using Structural Equation Modeling (SEM) from participants in the Chinese FinTech industry.

Findings & value added: Our empirical findings show that GenAI improves both kinds of innovations and, subsequently, leads to improved organizational performance. However, ethical dilemmas do not significantly affect either of these effects. Moreover, the study suggests that aligning GenAI adoption with ESG goals, such as promoting sustainable practices and ensuring ethical governance, can further enhance long-term performance and stakeholder trust. This study underlines the strategic role of GenAI adoption in driving innovation, advancing ESG objectives, and improving performance in the fast-evolving landscape of FinTech.

Downloads

Download data is not yet available.

References

Abrokwah-Larbi, K. (2023). The role of generative artificial intelligence (GAI) in customer personalisation (CP) development in SMEs: A theoretical framework and research propositions. Industrial Artificial Intelligence, 1(1), 11.
View in Google Scholar

Al-kfairy, M., Mustafa, D., Kshetri, N., Insiew, M., & Alfandi, O. (2024). Ethical challenges and solutions of generative AI: An interdisciplinary perspective. Informatics, 11(3), 58.
View in Google Scholar

Aldboush, H. H., & Ferdous, M. (2023). Building trust in fintech: An analysis of ethical and privacy considerations in the intersection of big data, AI, and customer trust. International Journal of Financial Studies, 11(3), 90.
View in Google Scholar

Almansour, M. (2023). Artificial intelligence and resource optimization: A study of Fintech start-ups. Resources Policy, 80, 103250.
View in Google Scholar

Almaqtari, F. A. (2024). The moderating role of IT governance on the relationship between FinTech and sustainability performance. Journal of Open Innovation: Technology, Market, and Complexity, 10(2), 100267.
View in Google Scholar

Aloulou, M., Grati, R., Al-Qudah, A. A., & Al-Okaily, M. (2024). Does FinTech adoption increase the diffusion rate of digital financial inclusion? A study of the banking industry sector. Journal of Financial Reporting and Accounting, 22(2), 289–307.
View in Google Scholar

Anshari, M., Almunawar, M. N., Masri, M., & Hrdy, M. (2021). Financial technology with AI-enabled and ethical challenges. Society, 58(3), 189–195.
View in Google Scholar

ARABI, S. (2024). AI and sustainability in Islamic banks: Crafting innovative solutions for major challenges. International Journal of Accounting, Finance, Auditing, Management and Economics, 5(8), 533–545.
View in Google Scholar

Arner, D. W., Buckley, R. P., Zetzsche, D. A., & Veidt, R. (2020). Sustainability, FinTech and financial inclusion. European Business Organization Law Review, 21, 7–35.
View in Google Scholar

Ashok, M., Madan, R., Joha, A., & Sivarajah, U. (2022). Ethical framework for artificial intelligence and digital technologies. International Journal of Information Management, 62, 102433.
View in Google Scholar

Aw, E. C.-X., Zha, T., & Chuah, S. H.-W. (2023). My new financial companion! Non-linear understanding of robo-advisory service acceptance. Service Industries Journal, 43(3-4), 185–212.
View in Google Scholar

Bagdi, H., & Bulsara, H. P. (2023). Understanding the role of perceived enjoyment, self-efficacy and system accessibility: Digital natives' online learning intentions. Journal of Applied Research in Higher Education.
View in Google Scholar

Bahoo, S., Cucculelli, M., & Qamar, D. (2023). Artificial intelligence and corporate innovation: A review and research agenda. Technological Forecasting and Social Change, 188, 122264.
View in Google Scholar

Barile, D., Secundo, G., & Bussoli, C. (2024). Exploring artificial intelligence robo-advisor in banking industry: A platform model. Management Decision.
View in Google Scholar

Bilgram, V., & Laarmann, F. (2023). Accelerating innovation with generative AI: AI-augmented digital prototyping and innovation methods. IEEE Engineering Management Review.
View in Google Scholar

Bisht, S., Sengupta, S., Tewari, I., Bisht, N., Pandey, K., & Upadhyay, A. (2024). AI-driven tools transforming the banking landscape: Revolutionizing finance. In 10th international conference on advanced computing and communication systems (ICACCS). IEEE.
View in Google Scholar

Borovkov, A., Rozhdestvenskiy, O., Pavlova, E., Glazunov, A., & Savichev, K. (2021). Key barriers of digital transformation of the high-technology manufacturing: An evaluation method. Sustainability, 13(20), 11153.
View in Google Scholar

Burger, B., Kanbach, D. K., Kraus, S., Breier, M., & Corvello, V. (2023). On the use of AI-based tools like ChatGPT to support management research. European Journal of Innovation Management, 26(7), 233–241.
View in Google Scholar

Camilleri, M. A. (2024). Artificial intelligence governance: Ethical considerations and implications for social responsibility. Expert Systems, 41(7), e13406.
View in Google Scholar

Chen, B., Wu, Z., & Zhao, R. (2023). From fiction to fact: The growing role of generative AI in business and finance. Journal of Chinese Economic and Business Studies, 21(4), 471–496.
View in Google Scholar

Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295–336.
View in Google Scholar

Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers.
View in Google Scholar

Cordasco, C., Gherhes, C., Brooks, C., & Vorley, T. (2021). An institutional taxonomy of adoption of innovation in the classic professions. Technovation, 107, 102272.
View in Google Scholar

Cui, Y. G., van Esch, P., & Phelan, S. (2024). How to build a competitive advantage for your brand using generative AI. Business Horizons.
View in Google Scholar

Culot, G., Podrecca, M., & Nassimbeni, G. (2024). Blockchain adoption and operational performance: A secondary data analysis on effects and contingencies. International Journal of Operations & Production Management, 44(13), 69–99.
View in Google Scholar

Cumming, D., Johan, S., & Reardon, R. (2023). Global fintech trends and their impact on international business: A review. Multinational Business Review, 31(3), 413–436.
View in Google Scholar

Dadabada, P. K. (2024). Analyzing the impact of ESG integration and FinTech innovations on green finance: A comparative case studies approach. Journal of the Knowledge Economy.
View in Google Scholar

David, L. K., Wang, J., David, V., & Angel, V. (2024). Fintech as a catalyst for innovation and sustainable growth: Analyzing the dynamics of R&D Investment in China. Asian Journal of Technology Innovation.
View in Google Scholar

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
View in Google Scholar

Dawood, H. M., Liew, C. Y., & Lau, T. C. (2021). Mobile perceived trust mediation on the intention and adoption of FinTech innovations using mobile technology: A systematic literature review. F1000Research, 10.
View in Google Scholar

Dijkstra, T. K., & Henseler, J. (2015). Consistent partial least squares path modeling. MIS Quarterly, 39(2), 297–316. https://www.jstor.org/stable/26628355.
View in Google Scholar

Ding, J., Li, L., & Zhao, J. (2024). How does fintech prompt corporations toward ESG sustainable development? Evidence from China. Energy Economics, 131, 107387.
View in Google Scholar

Dubey, R., Gunasekaran, A., Childe, S. J., Bryde, D. J., Giannakis, M., Foropon, C., Roubaud, D., Hazen, B. T. (2020). Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations. International Journal of Production Economics, 226, 107599.
View in Google Scholar

Ferilli, G. B., Palmieri, E., Miani, S., & Stefanelli, V. (2024). The impact of FinTech innovation on digital financial literacy in Europe: Insights from the banking industry. Research in International Business and Finance, 69, 102218.
View in Google Scholar

Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Los Angeles, CA: SAGE Publications Sage.
View in Google Scholar

Fosso Wamba, S., Guthrie, C., Queiroz, M. M., & Minner, S. (2023). ChatGPT and generative artificial intelligence: An exploratory study of key benefits and challenges in operations and supply chain management. International Journal of Production Research.
View in Google Scholar

Galeone, G., Ranaldo, S., & Fusco, A. (2024). ESG and FinTech: Are they connected? Research in International Business and Finance, 69, 102225.
View in Google Scholar

Gesk, T. S., & Leyer, M. (2022). Artificial intelligence in public services: When and why citizens accept its usage. Government Information Quarterly, 39(3), 101704.
View in Google Scholar

Gonzalez-Ruiz, J. D., Ospina Patiño, C., & Marín-Rodríguez, N. J. (2024). The influence of environmental, social, and governance issues in the banking industry. Administrative Sciences, 14(7), 156.
View in Google Scholar

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. New Jersey: Pearson Prentice Hall
View in Google Scholar

Hair Jr, J., Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.
View in Google Scholar

Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.
View in Google Scholar

Holzinger, A., Schweier, J., Gollob, C., Nothdurft, A., Hasenauer, H., Kirisits, T., Häggström, C., Visser, R., Cavalli, R., Spinelli, R., & Stampfer, K. (2024). From industry 5.0 to forestry 5.0: Bridging the gap with human-centered artificial intelligence. Current Forestry Reports, 10, 442–455.
View in Google Scholar

Horani, O. M., Al-Adwan, A. S., Yaseen, H., Hmoud, H., Al-Rahmi, W. M., & Alkhalifah, A. (2023). The critical determinants impacting artificial intelligence adoption at the organizational level. Information Development, 02666669231166889.
View in Google Scholar

Huang, T.-L., & Hsu Liu, F. (2014). Formation of augmented-reality interactive technology's persuasive effects from the perspective of experiential value. Internet Research, 24(1), 82–109.
View in Google Scholar

Iranmanesh, M., Lim, K. H., Foroughi, B., Hong, M. C., & Ghobakhloo, M. (2023). Determinants of intention to adopt big data and outsourcing among SMEs: Organisational and technological factors as moderators. Management Decision, 61(1), 201–222.
View in Google Scholar

Ismail, A., Ali, M. S., Alattar, K., Hasan, M., & Durrani, F. (2023). The role of artificial intelligence techniques in the digital transformation of Jordanian banking system. In Artificial intelligence (AI) and finance (pp. 72–82). Springer.
View in Google Scholar

J. Nair, A., Manohar, S., & Mittal, A. (2024). AI-enabled FinTech for innovative sustainability: Promoting organizational sustainability practices in digital accounting and finance. International Journal of Accounting & Information Management.
View in Google Scholar

Jan, Z., Ahamed, F., Mayer, W., Patel, N., Grossmann, G., Stumptner, M., & Kuusk, A. (2023). Artificial intelligence for industry 4.0: Systematic review of applications, challenges, and opportunities. Expert Systems with Applications, 216, 119456.
View in Google Scholar

Jansen, J. J., Van Den Bosch, F. A., & Volberda, H. W. (2006). Exploratory innovation, exploitative innovation, and performance: Effects of organizational antecedents and environmental moderators. Management Science, 52(11), 1661–1674.
View in Google Scholar

Jansen, J. J., Vera, D., & Crossan, M. (2009). Strategic leadership for exploration and exploitation: The moderating role of environmental dynamism. Leadership Quarterly, 20(1), 5–18.
View in Google Scholar

Kazachenok, O. P., Stankevich, G. V., Chubaeva, N. N., & Tyurina, Y. G. (2023). Economic and legal approaches to the humanization of FinTech in the economy of artificial intelligence through the integration of blockchain into ESG Finance. Humanities and Social Sciences Communications, 10(1), 1–9.
View in Google Scholar

Khalil, R. G., Damrah, S., Bajaher, M., & Shawtari, F. A. (2023). Unveiling the relationship of ESG, fintech, green finance, innovation and sustainability: Case of Gulf countries. Environmental Science and Pollution Research, 30(54), 116299–116312. DOI: 10.1007/s11356-023-30584-8.
View in Google Scholar

Kong, Y., Agyemang, A., Alessa, N., & Kongkuah, M. (2023). The moderating role of technological innovation on environment, social, and governance (ESG) performance and firm value: Evidence from developing and least-developed countries. Sustainability, 15(19), 14240.
View in Google Scholar

Kumar, B., Kumar, A., Sassanelli, C., & Kumar, L. (2024). Exploring the role of finance in driving circular economy and sustainable business practices. Journal of Cleaner Production, 486, 144480.
View in Google Scholar

Lai, K. P., & Langley, P. (2024). Playful finance: Gamification and intermediation in FinTech economies. Geoforum, 151, 103848.
View in Google Scholar

Lee, D. K. C., Guan, C., Yu, Y., & Ding, Q. (2024). A comprehensive review of generative AI in finance. FinTech, 3(3), 460–478.
View in Google Scholar

Lee, J., Serafin, A. M., & Courteau, C. (2023). Corporate disclosure, ESG and green fintech in the energy industry. Journal of World Energy Law & Business, 16(6), 473–491.
View in Google Scholar

Li, B., Du, J., Yao, T., & Wang, Q. (2023). FinTech and corporate green innovation: An external attention perspective. Finance Research Letters, 58, 104661.
View in Google Scholar

Liu, H., Chu, H., Huang, Q., & Chen, X. (2016). Enhancing the flow experience of consumers in China through interpersonal interaction in social commerce. Computers in Human Behavior, 58, 306–314.
View in Google Scholar

Lutfi, A., Alrawad, M., Alsyouf, A., Almaiah, M. A., Al-Khasawneh, A., Al-Khasawneh, A. L., Alshira'h, A. F., Alshirah, M. H., Saad, M., & Ibrahim, N. (2023). Drivers and impact of big data analytic adoption in the retail industry: A quantitative investigation applying structural equation modeling. Journal of Retailing and Consumer Services, 70, 103129.
View in Google Scholar

Makki, A. A., & Alqahtani, A. Y. (2022). Modeling the enablers to FinTech innovation in Saudi Arabia: A hybrid approach using ism and anp. Systems, 10(5), 181.
View in Google Scholar

March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87.
View in Google Scholar

March, J. G., & Shapira, Z. (1987). Managerial perspectives on risk and risk taking. Management Science, 33(11), 1404–1418.
View in Google Scholar

Mariani, M. M., Machado, I., & Nambisan, S. (2023). Types of innovation and artificial intelligence: A systematic quantitative literature review and research agenda. Journal of Business Research, 155, 113364.
View in Google Scholar

Maroufkhani, P., Iranmanesh, M., & Ghobakhloo, M. (2023). Determinants of big data analytics adoption in small and medium-sized enterprises (SMEs). Industrial Management & Data Systems, 123(1), 278–301.
View in Google Scholar

Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 2053951716679679.
View in Google Scholar

Moharrak, M., & Mogaji, E. (2024). Generative AI in banking: Empirical insights on integration, challenges and opportunities in a regulated industry. International Journal of Bank Marketing.
View in Google Scholar

Na, S., Heo, S., Han, S., Shin, Y., & Roh, Y. (2022). Acceptance model of artificial intelligence (AI)-based technologies in construction firms: Applying the Technology Acceptance Model (TAM) in combination with the Technology–Organisation–Environment (TOE) framework. Buildings, 12(2), 90.
View in Google Scholar

Nadeem, W., Alimamy, S., & Ashraf, A. R. (2023). Navigating through difficult times with ethical marketing: Assessing consumers' willingness-to-pay in the sharing economy. Journal of Retailing and Consumer Services, 70, 103150.
View in Google Scholar

Nannini, L., Marchiori Manerba, M., & Beretta, I. (2024). Mapping the landscape of ethical considerations in explainable AI research. Ethics and Information Technology, 26(3), 44.
View in Google Scholar

Narayanan, D., Nagpal, M., McGuire, J., Schweitzer, S., & De Cremer, D. (2024). Fairness perceptions of artificial intelligence: A review and path forward. International Journal of Human–Computer Interaction, 40(1), 4–23.
View in Google Scholar

Nguyen, D. K., Sermpinis, G., & Stasinakis, C. (2023). Big data, artificial intelligence and machine learning: A transformative symbiosis in favour of financial technology. European Financial Management, 29(2), 517–548.
View in Google Scholar

Nowakowski, M. (2022). Ethical FinTech: The importance of ethics in creating secure financial products and services. In Digital transformation and the economics of banking (pp. 81–98). Routledge.
View in Google Scholar

Nunnally, J. C., & Bernstein, I. (1978). Psychometric theory. New York: McGrawHill.
View in Google Scholar

Offiong, U. P., Szopik-Depczyńska, K., Cheba, K., & Ioppolo, G. (2024). FinTech as a digital innovation in microfinance companies–systematic literature review. European Journal of Innovation Management, 27(9), 562–581.
View in Google Scholar

Olan, F., Arakpogun, E. O., Suklan, J., Nakpodia, F., Damij, N., & Jayawickrama, U. (2022). Artificial intelligence and knowledge sharing: Contributing factors to organizational performance. Journal of Business Research, 145, 605–615.
View in Google Scholar

Omarini, A. (2020). FinTech: A new hedge for a financial re-intermediation. Strategy and risk perspectives. Frontiers in Artificial Intelligence, 3, 63.
View in Google Scholar

Ooi, K.-B., Tan, G. W.-H., Al-Emran, M., Al-Sharafi, M. A., Capatina, A., Chakraborty, A., Dwivedi, Y. K., Huang, T. L., Kar, A. K., Lee, V. H., Loh, X. M., Micu, A., Mikalef, P., Mogaji, E. Pandey, N., Raman, R., Rana, N. P., Sarker, P. Sharma, A., Teng, C. I., Wamba, S. F., & Wong, L. W. (2023). The potential of generative artificial intelligence across disciplines: Perspectives and future directions. Journal of Computer Information Systems.
View in Google Scholar

Palmieri, E., & Geretto, E. F. (2024). ESG innovation in the financial industry. In Adapting to change: ESG and alternative finance in shaping the bank-firm relationship (pp. 63–95): Springer.
View in Google Scholar

Piotrowski, D., & Orzeszko, W. (2023). Artificial intelligence and customers’ intention to use robo-advisory in banking services. Equilibrium. Quarterly Journal of Economics and Economic Policy, 18(4), 967–1007.
View in Google Scholar

Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879.
View in Google Scholar

Prasad Agrawal, K. (2023). Organizational sustainability of generative AI-driven optimization intelligence. Journal of Computer Information Systems.
View in Google Scholar

Prasad Agrawal, K. (2024). Towards adoption of generative AI in organizational settings. Journal of Computer Information Systems, 64(5), 636–651.
View in Google Scholar

Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891.
View in Google Scholar

Qureshi, N. I., Choudhuri, S. S., Nagamani, Y., Varma, R. A., & Shah, R. (2024). Ethical considerations of AI in financial services: Privacy, bias, and algorithmic transparency. In International conference on knowledge engineering and communication systems (ICKECS). IEEE.
View in Google Scholar

Rabbani, M. R., Sarea, A., Khan, S., & Abdullah, Y. (2022). Ethical concerns in artificial intelligence (AI): The role of RegTech and Islamic finance. In Artificial intelligence for sustainable finance and sustainable technology: Proceedings of ICGER 2021. Springer.
View in Google Scholar

Rahman, M., Ming, T. H., Baigh, T. A., & Sarker, M. (2023). Adoption of artificial intelligence in banking services: An empirical analysis. International Journal of Emerging Markets, 18(10), 4270–4300.
View in Google Scholar

Rasouli, N., Rasoolimanesh, S. M., Rahmani, A. K., Momayez, A., & Torabi, M. A. (2022). Effects of customer forgiveness on brand betrayal and brand hate in restaurant service failures: does apology letter matter? Journal of Hospitality Marketing & Management, 31(6), 662–687.
View in Google Scholar

Reinartz, W., Haenlein, M., & Henseler, J. (2009). An empirical comparison of the efficacy of covariance-based and variance-based SEM. International Journal of research in Marketing, 26(4), 332–344.
View in Google Scholar

Reyes-Mercado, P. (2021). Dynamics of Fintech and the broad financial industry. In FinTech strategy. Palgrave studies in democracy, innovation, and entrepreneurship for growth. Palgrave Macmillan.
View in Google Scholar

Ridzuan, N. N., Masri, M., Anshari, M., Fitriyani, N. L., & Syafrudin, M. (2024). AI in the financial sector: The line between innovation, regulation and ethical responsibility. Information, 15(8), 432.
View in Google Scholar

Rossi, A. G., & Utkus, S. P. (2020). The needs and wants in financial advice: Human versus robo-advising. SSRN, 3759041. http://dx.doi.org/10.2139/ssrn.3759041.
View in Google Scholar

Sedkaoui, S., & Benaichouba, R. (2024). Generative AI as a transformative force for innovation: A review of opportunities, applications and challenges. European Journal of Innovation Management.
View in Google Scholar

Shala, A., & Berisha, V. (2024). The impact of Fintech on the achievement of environmental, social, and governance (ESG) goals. In Sustainable Development Goals: The impact of sustainability measures on wellbeing (pp. 55–77). Emerald Publishing Limited.
View in Google Scholar

Sharma, S., Islam, N., Singh, G., & Dhir, A. (2022). Why do retail customers adopt artificial intelligence (AI) based autonomous decision-making systems? IEEE Transactions on Engineering Management, 71, 1846–1861.
View in Google Scholar

Sharma, S., Singh, G., Islam, N., & Dhir, A. (2022). Why do SMEs adopt artificial intelligence-based chatbots? IEEE Transactions on Engineering Management, 71, 1773–1786.
View in Google Scholar

Shi, Y., Van Toorn, C., & McEwan, M. (2024). Exploration–exploitation: How business analytics powers organisational ambidexterity for environmental sustainability. Information Systems Journal, 34(3), 894–930.
View in Google Scholar

So, M. K. (2021). Robo-advising risk profiling through content analysis for sustainable development in the Hong Kong financial market. Sustainability, 13(3), 1306.
View in Google Scholar

Subburayan, B., Sankarkumar, A. V., Singh, R., & Mushi, H. M. (2024). Transforming of the financial landscape from 4.0 to 5.0: Exploring the integration of blockchain, and artificial intelligence.In Applications of block chain technology and artificial intelligence (pp. 137–161). Springer.
View in Google Scholar

Sun, X., & Xie, X. (2024). How does digital finance promote entrepreneurship? The roles of traditional financial institutions and BigTech firms. Pacific-Basin Finance Journal, 85, 102316.
View in Google Scholar

Svetlova, E. (2022). AI ethics and systemic risks in finance. AI and Ethics, 2(4), 713–725.
View in Google Scholar

Tan, W., Cai, Y., Luo, H., Zhou, M., & Shen, M. (2024). ESG, technological innovation and firm value: evidence from china. International Review of Financial Analysis, 96, 103546.
View in Google Scholar

Tristan, L. (2023). Environmental, social, and governance (ESG) and artificial intelligence in finance: State-of-the-art and research takeaways. Research Square.
View in Google Scholar

Tsamados, A., Aggarwal, N., Cowls, J., Morley, J., Roberts, H., Taddeo, M., & Floridi, L. (2021). The ethics of algorithms: key problems and solutions. In Ethics, governance, and policies in artificial intelligence (pp. 97–123). Springer.
View in Google Scholar

Verma, S., & Garg, N. (2023). Development and validation of techno-ethical orientation scale for Indian post-millennial students. Journal of Science and Technology Policy Management.
View in Google Scholar

wael AL-khatib, A. (2023). Drivers of generative artificial intelligence to fostering exploitative and exploratory innovation: A TOE framework. Technology in Society, 75, 102403.
View in Google Scholar

Wu, R., & Yu, Z. (2024). Investigating users’ acceptance of the metaverse with an extended technology acceptance model. International Journal of Human–Computer Interaction, 40(19), 5810–5826.
View in Google Scholar

Xu, Y., & Zhu, N. (2024). The effect of environmental, social, and governance (ESG) performance on corporate financial performance in China: Based on the perspective of innovation and financial sonstraints. Sustainability, 16(8), 3329.
View in Google Scholar

Yan, C., Siddik, A. B., Akter, N., & Dong, Q. (2021). Factors influencing the adoption intention of using mobile financial service during the COVID-19 pandemic: The role of FinTech. Environmental Science and Pollution Research.
View in Google Scholar

Yang, Q., & Lee, Y.-C. (2024). Ethical AI in financial inclusion: The role of algorithmic fairness on user satisfaction and recommendation. Big Data and Cognitive Computing, 8(9), 105.
View in Google Scholar

Zahoor, N., Khan, Z., Marinova, S., & Cui, L. (2024). Ambidexterity in strategic alliances: An integrative review of the literature. International Journal of Management Reviews, 26(1), 82–109.
View in Google Scholar

Zeng, L., Li, H., Lin, L., Hu, D. J. J., & Liu, H. (2024). ESG standards in China: Bibliometric analysis, development status research, and future research directions. Sustainability, 16(16), 7134.
View in Google Scholar

Zohny, H., McMillan, J., & King, M. (2023). Ethics of generative AI. Journal of Medical Ethics, 49, 79–80.
View in Google Scholar

Downloads

Published

30-12-2024

Issue

Section

Articles

How to Cite

Zada, M., Khan , S., Mehmood, S., & Contreras-Barraza, N. (2024). Generative artificial intelligence in FinTech: Applications, environmental, social, and governance considerations, and organizational performance: The moderating role of ethical dilemmas. Oeconomia Copernicana, 15(4), 1303-1347. https://doi.org/10.24136/oc.3323

Similar Articles

1-10 of 197

You may also start an advanced similarity search for this article.